Journal of Diabetes Science and Technology最新文献

{"title":"Improvement in Protective Sensation: Clinical Evidence From a Randomized Controlled Trial for Treatment of Painful Diabetic Neuropathy With 10 kHz Spinal Cord Stimulation.","authors":"Charles E Argoff, David G Armstrong, Zachary B Kagan, Michael J Jaasma, Manish Bharara, Kerry Bradley, David L Caraway, Erika A Petersen","doi":"10.1177/19322968231222271","DOIUrl":"10.1177/19322968231222271","url":null,"abstract":"<p><strong>Background: </strong>Painful diabetic neuropathy (PDN) can result in the loss of protective sensation, in which people are at twice the likelihood of foot ulceration and three times the risk of lower extremity amputation. Here, we evaluated the long-term effects of high-frequency (10 kHz) paresthesia-independent spinal cord stimulation (SCS) on protective sensation in the feet and the associated risk of foot ulceration for individuals with PDN.</p><p><strong>Methods: </strong>The SENZA-PDN clinical study was a randomized, controlled trial in which 216 participants with PDN were randomized to receive either conventional medical management (CMM) alone or 10 kHz SCS plus CMM, with optional treatment crossover after 6 months. At study visits (baseline through 24 months), 10-g monofilament sensory assessments were conducted at 10 locations per foot. Two published methods were used to evaluate protective sensation via classifying risk of foot ulceration.</p><p><strong>Results: </strong>Participants in the 10 kHz SCS group reported increased numbers of sensate locations as compared to CMM alone (<i>P</i> < .001) and to preimplantation (<i>P</i> < .01) and were significantly more likely to be at low risk of foot ulceration using both classification methods. The proportion of low-risk participants approximately doubled from preimplantation to 3 months postimplantation and remained stable through 24 months (<i>P</i> ≤ .01).</p><p><strong>Conclusions: </strong>Significant improvements were observed in protective sensation from preimplantation to 24 months postimplantation for the 10 kHz SCS group. With this unique, disease-modifying improvement in sensory function, 10 kHz SCS provides the potential to reduce ulceration, amputation, and other severe sequelae of PDN.</p><p><strong>Trial registration: </strong>The SENZA-PDN study is registered on ClinicalTrials.gov with identifier NCT03228420.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"992-998"},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571436/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139403114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Practical Considerations and Implementation of Automated Insulin Delivery Systems.","authors":"Laurel H Messer, Gregory P Forlenza, Linda Gonder-Frederick, Korey Hood, Osagie Ebekozien, Katharine Barnard-Kelly, Lori M Laffel, Jennifer L Sherr, Rayhan Lal, Stuart A Weinzimer","doi":"10.1177/19322968251335971","DOIUrl":"10.1177/19322968251335971","url":null,"abstract":"<p><p>The technological progress to date with automated insulin delivery (AID) has ushered in a new era of challenges and opportunities for people with diabetes (PWD), spotlighting implementation considerations. Beyond physiologic and technologic variation, cost, access, and health care professional (HCP) endorsement/experience lead to uneven uptake of AID technologies and attenuate universal ease of use. For AID to be broadly implemented, we must prioritize the lived experience for PWD and consider how to alleviate burden to promote physical/functional health, psychological well-being, and social well-being. Expectations and education help HCPs and PWD navigate the similarities and differences between AID devices, and help find common ties: users need to give the system time to work, learn to trust it, and not try to \"trick\" the system. Despite these learnings, disparities in uptake exist, both in clinical trials and in routine clinical care. Strategies to proactively address AID disparities must be enacted at multiple levels, including recognizing HCP biases, using clinic-based benchmarking efforts, and addressing insurance and policy barriers, all of which increase in importance as AID becomes more common for people with type 2 diabetes. Furthermore, broader implementation will require comprehensive health care system integration efforts, including new data solutions. Overall, the success of AID requires ongoing transformation of clinical paradigms, with lockstep alignment between PWD and their families, health care professionals, researchers, funders, policy makers, and industry partners.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":"19 4","pages":"950-957"},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12213529/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144540371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retrospective Comparison of Commercially Available Automated Insulin Delivery With Open-Source Automated Insulin Delivery Systems in Type 1 Diabetes.","authors":"Anna Schütz, Birgit Rami-Merhar, Ingrid Schütz-Fuhrmann, Nicole Blauensteiner, Petra Baumann, Tina Pöttler, Julia K Mader","doi":"10.1177/19322968241230106","DOIUrl":"10.1177/19322968241230106","url":null,"abstract":"<p><strong>Background: </strong>Automated insulin delivery (AID) systems have shown to improve glycemic control in a range of populations and settings. At the start of this study, only one commercial AID system had entered the Austrian market (MiniMed 670G, Medtronic). However, there is an ever-growing community of people living with type 1 diabetes (PWT1D) using open-source (OS) AID systems.</p><p><strong>Materials and methods: </strong>A total of 144 PWT1D who used either the MiniMed 670G (670G) or OS-AID systems routinely for a period of at least three to a maximum of six months, between February 18, 2020 and January 15, 2023, were retrospectively analyzed (116 670G aged from 2.6 to 71.8 years and 28 OS-AID aged from 3.4 to 53.5 years). The goal is to evaluate and compare the quality of glycemic control of commercially available AID and OS-AID systems and to present all data by an in-depth descriptive analysis of the population. No statistical tests were performed.</p><p><strong>Results: </strong>The PWT1D using OS-AID systems spent more time in range (TIR)_{70-180 mg/dL} (81.7% vs 73.9%), less time above range (TAR)_{181-250 mg/dL} (11.1% vs 19.6%), less TAR_{>250 mg/dL} (2.5% vs 4.3%), and more time below range (TBR)_{54-69 mg/dL} (2.2% vs 1.7%) than PWT1D using the 670G system. The TBR_{<54 mg/dL} was comparable in both groups (0.3% vs 0.4%). In the OS-AID group, median glucose level and glycated hemoglobin (HbA1c) were lower than in the 670G system group (130 vs 150 mg/dL; 6.2% vs 7.0%).</p><p><strong>Conclusion: </strong>In conclusion, both groups were able to achieve satisfactory glycemic outcomes independent of age, gender, and diabetes duration. However, the PWT1D using OS-AID systems attained an even better glycemic control with no clinical safety concerns.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1060-1067"},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571566/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139746736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Affecting Reproducibility of Change in Glucose During Exercise: Results From the Type 1 Diabetes and EXercise Initiative.","authors":"Zoey Li, Peter Calhoun, Michael R Rickels, Robin L Gal, Roy W Beck, Peter G Jacobs, Mark A Clements, Susana R Patton, Jessica R Castle, Corby K Martin, Melanie B Gillingham, Francis J Doyle, Michael C Riddell","doi":"10.1177/19322968241234687","DOIUrl":"10.1177/19322968241234687","url":null,"abstract":"<p><strong>Aims: </strong>To evaluate factors affecting within-participant reproducibility in glycemic response to different forms of exercise.</p><p><strong>Methods: </strong>Structured exercise sessions ~30 minutes in length from the Type 1 Diabetes Exercise Initiative (T1DEXI) study were used to assess within-participant glycemic variability during and after exercise. The effect of several pre-exercise factors on the within-participant glycemic variability was evaluated.</p><p><strong>Results: </strong>Data from 476 adults with type 1 diabetes were analyzed. A participant's change in glucose during exercise was reproducible within 15 mg/dL of the participant's other exercise sessions only 32% of the time. Participants who exercised with lower and more consistent glucose level, insulin on board (IOB), and carbohydrate intake at exercise start had less variability in glycemic change during exercise. Participants with lower mean glucose (<i>P</i> < .001), lower glucose coefficient of variation (CV) (<i>P</i> < .001), and lower % time <70 mg/dL (<i>P</i> = .005) on sedentary days had less variable 24-hour post-exercise mean glucose.</p><p><strong>Conclusions: </strong>Reproducibility of change in glucose during exercise was low in this cohort of adults with T1D, but more consistency in pre-exercise glucose levels, IOB, and carbohydrates may increase this reproducibility. Mean glucose variability in the 24 hours after exercise is influenced more by the participant's overall glycemic control than other modifiable factors.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"958-970"},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571421/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140059553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Auto-correction Boluses Contribute to Hypoglycemia Following Temporary Target Cessation During Hyperglycemia.","authors":"Andrew Welch, Rabia Zulfiqar, Erin Black, Mercedes Falciglia","doi":"10.1177/19322968251336187","DOIUrl":"10.1177/19322968251336187","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1158-1159"},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12021852/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143987822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FDA Interoperability Designation-Creating Options for People With Diabetes and Pump Companies: Regulatory, Technological, and Commercial Perspectives.","authors":"David C Klonoff, Cindy N Ho, Alessandra Ayers, Aiman Abdel-Malek","doi":"10.1177/19322968241271304","DOIUrl":"10.1177/19322968241271304","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"869-874"},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571429/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142288369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk Prediction of Diabetic Foot Amputation Using Machine Learning and Explainable Artificial Intelligence.","authors":"Chien Wei Oei, Yam Meng Chan, Xiaojin Zhang, Kee Hao Leo, Enming Yong, Rhan Chaen Chong, Qiantai Hong, Li Zhang, Ying Pan, Glenn Wei Leong Tan, Malcolm Han Wen Mak","doi":"10.1177/19322968241228606","DOIUrl":"10.1177/19322968241228606","url":null,"abstract":"<p><strong>Background: </strong>Diabetic foot ulcers (DFUs) are serious complications of diabetes which can lead to lower extremity amputations (LEAs). Risk prediction models can identify high-risk patients who can benefit from early intervention. Machine learning (ML) methods have shown promising utility in medical applications. Explainable modeling can help its integration and acceptance. This study aims to develop a risk prediction model using ML algorithms with explainability for LEA in DFU patients.</p><p><strong>Methods: </strong>This study is a retrospective review of 2559 inpatient DFU episodes in a tertiary institution from 2012 to 2017. Fifty-one features including patient demographics, comorbidities, medication, wound characteristics, and laboratory results were reviewed. Outcome measures were the risk of major LEA, minor LEA and any LEA. Machine learning models were developed for each outcome, with model performance evaluated using receiver operating characteristic (ROC) curves, balanced-accuracy and F1-score. SHapley Additive exPlanations (SHAP) was applied to interpret the model for explainability.</p><p><strong>Results: </strong>Model performance for prediction of major, minor, and any LEA event achieved ROC of 0.820, 0.637, and 0.756, respectively, with XGBoost, XGBoost, and Gradient Boosted Trees algorithms demonstrating best results for each model, respectively. Using SHAP, key features that contributed to the predictions were identified for explainability. Total white cell (TWC) count, comorbidity score and red blood cell count contributed highest weightage to major LEA event. Total white cell, eosinophils, and necrotic eschar in the wound contributed most to any LEA event.</p><p><strong>Conclusions: </strong>Machine learning algorithms performed well in predicting the risk of LEA in a patient with DFU. Explainability can help provide clinical insights and identify at-risk patients for early intervention.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1008-1022"},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571574/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139576118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Environment, Climate, and Diabetes: An International Topic.","authors":"Lutz Heinemann, David C Klonoff","doi":"10.1177/19322968251314841","DOIUrl":"10.1177/19322968251314841","url":null,"abstract":"<p><p>Every person with diabetes is affected by changes in the environment and climate. At the same time, the therapy of many people itself has a negative impact on these factors. One might assume that the relevant professional associations and health organizations, as well as health policymakers, have initiated appropriate activities. The manufacturers of antidiabetic drugs and medical devices used in diabetes therapy are aware of the problems at hand. To what extent they really implement changes in the production, storage, and transport of their products is not easy to assess. In summary, it should be said that the importance of environmental factors for people with diabetes and their therapy is probably still not sufficiently recognized.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1132-1136"},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11775938/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143052638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Workshop on Noninvasive Glucose Monitoring 2024.","authors":"Jeon Woong Kang, Mark A Arnold, Devin Steenkamp, Mark A Tapsak, Werner Mäntele, Yoonho Khang, Miyeon Jue, Peter T C So","doi":"10.1177/19322968251329371","DOIUrl":"10.1177/19322968251329371","url":null,"abstract":"<p><p>This first workshop on noninvasive glucose monitoring (NIGM) was held at the Massachusetts Institute of Technology (MIT) on October 30, 2024. Six invited speakers, representing industry, academia, and clinics, gave presentations that covered (1) an overview of the NIGM technologies, (2) the state of the art in NIGM technologies, such as near-infrared (NIR), mid-infrared (IR), photoacoustic, and Raman spectroscopies, (3) minimally invasive implantable continuous glucose monitoring (CGM) sensors, and (4) a clinician's perspective on the impact of the current CGM devices for patient care.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1144-1149"},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143730252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cost-Effectiveness of Closed-Loop Automated Insulin Delivery Using the Cambridge Hybrid Algorithm in Children and Adolescents With Type 1 Diabetes: Results from a Multicenter 6-Month Randomized Trial.","authors":"D Steven Fox, Julia Ware, Charlotte K Boughton, Janet M Allen, Malgorzata E Wilinska, Martin Tauschmann, Louise Denvir, Ajay Thankamony, Fiona Campbell, R Paul Wadwa, Bruce A Buckingham, Nikki Davis, Linda A DiMeglio, Nelly Mauras, Rachel E J Besser, Atrayee Ghatak, Stuart A Weinzimer, Lauren Kanapka, Craig Kollman, Judy Sibayan, Roy W Beck, Korey K Hood, Roman Hovorka","doi":"10.1177/19322968241231950","DOIUrl":"10.1177/19322968241231950","url":null,"abstract":"<p><strong>Background/objective: </strong>The main objective of this study is to evaluate the incremental cost-effectiveness (ICER) of the Cambridge hybrid closed-loop automated insulin delivery (AID) algorithm versus usual care for children and adolescents with type 1 diabetes (T1D).</p><p><strong>Methods: </strong>This multicenter, binational, parallel-controlled trial randomized 133 insulin pump using participants aged 6 to 18 years to either AID (n = 65) or usual care (n = 68) for 6 months. Both within-trial and lifetime cost-effectiveness were analyzed. Analysis focused on the treatment subgroup (n = 21) who received the much more reliable CamAPS FX hardware iteration and their contemporaneous control group (n = 24). Lifetime complications and costs were simulated via an updated Sheffield T1D policy model.</p><p><strong>Results: </strong>Within-trial, both groups had indistinguishable and statistically unchanged health-related quality of life, and statistically similar hypoglycemia, severe hypoglycemia, and diabetic ketoacidosis (DKA) event rates. Total health care utilization was higher in the treatment group. Both the overall treatment group and CamAPS FX subgroup exhibited improved HbA_1C (-0.32%, 95% CI: -0.59 to -0.04; <i>P</i> = .02, and -1.05%, 95% CI: -1.43 to -0.67; <i>P</i> < .001, respectively). Modeling projected increased expected lifespan of 5.36 years and discounted quality-adjusted life years (QALYs) of 1.16 (U.K. tariffs) and 1.52 (U.S. tariffs) in the CamAPS FX subgroup. Estimated ICERs for the subgroup were £19 324/QALY (United Kingdom) and -$3917/QALY (United States). For subgroup patients already using continuous glucose monitors (CGM), ICERs were £10 096/QALY (United Kingdom) and -$33 616/QALY (United States). Probabilistic sensitivity analysis generated mean ICERs of £19 342/QALY (95% CI: £15 903/QALY to £22 929/QALY) (United Kingdom) and -$28 283/QALY (95% CI: -$59 607/QALY to $1858/QALY) (United States).</p><p><strong>Conclusions: </strong>For children and adolescents with T1D on insulin pump therapy, AID using the Cambridge algorithm appears cost-effective below a £20 000/QALY threshold (United Kingdom) and cost saving (United States).</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"982-991"},"PeriodicalIF":3.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571777/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140143634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}